code: def testSchurComplementWithPrecomputedDivisor(self):
      base_kernel = exponentiated_quadratic.ExponentiatedQuadratic(
          [1.0, 2.0]
      )
      fixed_inputs = tf.ones([0, 2], np.float32)
      schur = schur_complement.SchurComplement(
          base_kernel, fixed_inputs
      )
      schur_with_divisor = (
          schur_complement.SchurComplement.with_precomputed_divisor(
              base_kernel, fixed_inputs
          )
      )
  
      x = np.ones([4, 3], np.float32)
      y = np.ones([5, 3], np.float32)
  
      self.assertAllClose(
          self.evaluate(schur_with_divisor.matrix(x, y)),
          self.evaluate(schur.matrix(x, y)),
      )
  
imports: import functools
  import itertools
  from unittest import mock
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import cholesky_util
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math.psd_kernels import exponentiated_quadratic
  from tensorflow_probability.python.math.psd_kernels import schur_complement
  from tensorflow_probability.python.math.psd_kernels.internal import test_util
label_desc: Use image node_id 9 for calling the SchurComplementTest obj's underlying member method code with example usage: obj.testSchurComplementWithPrecomputedDivisor() without return types